Accurate data-driven sliding mode parking control for autonomous ground vehicles with efficient trajectory planning in dynamic industrial scenarios-Reference-Cited by-同舟云学术

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Accurate data-driven sliding mode parking control for autonomous ground vehicles with efficient trajectory planning in dynamic industrial scenarios

Published:2024-05-10 Issue:13 Volume:112 Page:11195-11216
ISSN:0924-090X
Container-title:Nonlinear Dynamics
language:en
Short-container-title:Nonlinear Dyn

Author:

Jiang Liquan,Deng Yuxuan,Jiang Zhihui,He Ruhan,Yu Hao,Xu Weilin,Meng Jie^ORCID

Funder

National Nature Science Foundation of China

Key Technologies Research and Development Program

Hubei Provincial Engineering Research Center for Intelligent Textile and Fashion

Shuguang Program of Wuhan, China

Publisher

Springer Science and Business Media LLC

Link

https://link.springer.com/content/pdf/10.1007/s11071-024-09657-x.pdf

Reference43 articles.

1. Chai, R., Tsourdos, A., Chai, S., et al.: Multiphase overtaking maneuver planning for autonomous ground vehicles via a desensitized trajectory optimization approach. IEEE Trans. Ind. Inform. 19(1), 74–87 (2022)

2. Cai, X., Shi, K., Sun, Y., et al.: Dual-channel NCSs performance error estimation under DoS attacks and intelligent control supervised by machine learning to AGV application. IEEE Trans. Transp. Electrif. (2023). https://doi.org/10.1109/TTE.2023.3328305

3. He, X., Geng, Z.: Arbitrary point-to-point stabilization control in specified finite time for wheeled mobile robots based on dynamic model. Nonlinear Dyn. 97, 937–954 (2019)

4. De Ryck, M., Versteyhe, M., Debrouwere, F.: Automated guided vehicle systems, state-of-the-art control algorithms and techniques. J. Manuf. Syst. 54, 152–173 (2020)

5. Li, L., Jiang, L., Tu, W., et al.: Smooth and efficient path planning for car-like mobile robot using improved ant colony optimization in narrow and large-size scenes. Fractal Fract. 8(3), 157 (2024)

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